【PIR API adaptor No.260、274-278、292】 Migrate some ops into pir (#60172)

MarioLulab · web-flow · commit 69346324d97d · 2023-12-22T16:38:17.000+08:00
diff --git a/python/paddle/audio/functional/functional.py b/python/paddle/audio/functional/functional.py
@@ -17,11 +17,13 @@
 
 import paddle
 from paddle import Tensor
+from paddle.base.framework import Variable
+from paddle.pir import Value
 
 
 def hz_to_mel(
-    freq: Union[Tensor, float], htk: bool = False
-) -> Union[Tensor, float]:
+    freq: Union[Tensor, Value, Variable, float], htk: bool = False
+) -> Union[Tensor, Value, Variable, float]:
     """Convert Hz to Mels.
 
     Args:
@@ -43,7 +45,7 @@ def hz_to_mel(
     """
 
     if htk:
-        if isinstance(freq, Tensor):
+        if isinstance(freq, (Tensor, Variable, Value)):
             return 2595.0 * paddle.log10(1.0 + freq / 700.0)
         else:
             return 2595.0 * math.log10(1.0 + freq / 700.0)
@@ -60,7 +62,7 @@ def hz_to_mel(
     min_log_mel = (min_log_hz - f_min) / f_sp  # same (Mels)
     logstep = math.log(6.4) / 27.0  # step size for log region
 
-    if isinstance(freq, Tensor):
+    if isinstance(freq, (Tensor, Variable, Value)):
         target = (
             min_log_mel + paddle.log(freq / min_log_hz + 1e-10) / logstep
         )  # prevent nan with 1e-10
@@ -76,8 +78,8 @@ def hz_to_mel(
 
 
 def mel_to_hz(
-    mel: Union[float, Tensor], htk: bool = False
-) -> Union[float, Tensor]:
+    mel: Union[float, Tensor, Variable, Value], htk: bool = False
+) -> Union[float, Tensor, Variable, Value]:
     """Convert mel bin numbers to frequencies.
 
     Args:
@@ -108,7 +110,7 @@ def mel_to_hz(
     min_log_hz = 1000.0  # beginning of log region (Hz)
     min_log_mel = (min_log_hz - f_min) / f_sp  # same (Mels)
     logstep = math.log(6.4) / 27.0  # step size for log region
-    if isinstance(mel, Tensor):
+    if isinstance(mel, (Tensor, Variable, Value)):
         target = min_log_hz * paddle.exp(logstep * (mel - min_log_mel))
         mask = (mel > min_log_mel).astype(mel.dtype)
         freqs = target * mask + freqs * (
@@ -126,7 +128,7 @@ def mel_frequencies(
     f_max: float = 11025.0,
     htk: bool = False,
     dtype: str = 'float32',
-) -> Tensor:
+) -> Union[Tensor, Variable, Value]:
     """Compute mel frequencies.
 
     Args:
@@ -257,11 +259,11 @@ def compute_fbank_matrix(
 
 
 def power_to_db(
-    spect: Tensor,
+    spect: Union[Tensor, Variable, Value],
     ref_value: float = 1.0,
     amin: float = 1e-10,
     top_db: Optional[float] = 80.0,
-) -> Tensor:
+) -> Union[Tensor, Variable, Value]:
     """Convert a power spectrogram (amplitude squared) to decibel (dB) units. The function computes the scaling `10 * log10(x / ref)` in a numerically stable way.
 
     Args:
diff --git a/python/paddle/fft.py b/python/paddle/fft.py
@@ -21,7 +21,7 @@
 from . import _C_ops
 from .base.data_feeder import check_variable_and_dtype
 from .base.layer_helper import LayerHelper
-from .framework import in_dynamic_mode
+from .framework import in_dynamic_or_pir_mode
 from .tensor.attribute import is_floating_point, is_integer
 from .tensor.creation import _complex_to_real_dtype, _real_to_complex_dtype
 
@@ -1404,7 +1404,7 @@ def fft_c2c(x, n, axis, norm, forward, name):
         s = [n]
         x = _resize_fft_input(x, s, axes)
 
-    if in_dynamic_mode():
+    if in_dynamic_or_pir_mode():
         out = _C_ops.fft_c2c(x, axes, norm, forward)
     else:
         op_type = 'fft_c2c'
@@ -1435,7 +1435,7 @@ def fft_r2c(x, n, axis, norm, forward, onesided, name):
         _check_fft_n(n)
         s = [n]
         x = _resize_fft_input(x, s, axes)
-    if in_dynamic_mode():
+    if in_dynamic_or_pir_mode():
         out = _C_ops.fft_r2c(x, axes, norm, forward, onesided)
     else:
         op_type = 'fft_r2c'
@@ -1478,7 +1478,7 @@ def fft_c2r(x, n, axis, norm, forward, name):
         s = [n // 2 + 1]
         x = _resize_fft_input(x, s, axes)
 
-    if in_dynamic_mode():
+    if in_dynamic_or_pir_mode():
         if n is not None:
             out = _C_ops.fft_c2r(x, axes, norm, forward, n)
         else:
@@ -1537,7 +1537,7 @@ def fftn_c2c(x, s, axes, norm, forward, name):
     if s is not None:
         x = _resize_fft_input(x, s, axes)
 
-    if in_dynamic_mode():
+    if in_dynamic_or_pir_mode():
         out = _C_ops.fft_c2c(x, axes, norm, forward)
     else:
         op_type = 'fft_c2c'
@@ -1587,7 +1587,7 @@ def fftn_r2c(x, s, axes, norm, forward, onesided, name):
     if s is not None:
         x = _resize_fft_input(x, s, axes)
 
-    if in_dynamic_mode():
+    if in_dynamic_or_pir_mode():
         out = _C_ops.fft_r2c(x, axes, norm, forward, onesided)
     else:
         op_type = 'fft_r2c'
@@ -1651,7 +1651,7 @@ def fftn_c2r(x, s, axes, norm, forward, name):
         fft_input_shape[-1] = fft_input_shape[-1] // 2 + 1
         x = _resize_fft_input(x, fft_input_shape, axes)
 
-    if in_dynamic_mode():
+    if in_dynamic_or_pir_mode():
         if s is not None:
             out = _C_ops.fft_c2r(x, axes, norm, forward, s[-1])
         else:
diff --git a/python/paddle/nn/functional/activation.py b/python/paddle/nn/functional/activation.py
@@ -1494,7 +1494,7 @@ def mish(x, name=None):
             Tensor(shape=[3], dtype=float32, place=Place(cpu), stop_gradient=True,
             [-0.03357624,  0.        ,  4.99955177])
     """
-    if in_dynamic_mode():
+    if in_dynamic_or_pir_mode():
         return _C_ops.mish(x, 20)
     else:
         check_variable_and_dtype(
diff --git a/test/legacy_test/test_activation_op.py b/test/legacy_test/test_activation_op.py
@@ -4662,12 +4662,12 @@ def init_shape(self):
         self.shape = [10, 12]
 
     def test_check_output(self):
-        self.check_output()
+        self.check_output(check_pir=True)
 
     def test_check_grad(self):
         if self.dtype == np.float16:
             return
-        self.check_grad(['X'], 'Out')
+        self.check_grad(['X'], 'Out', check_pir=True)
 
 
 class TestMish_ZeroDim(TestMish):
@@ -4686,6 +4686,7 @@ def setUp(self):
             else paddle.CPUPlace()
         )
 
+    @test_with_pir_api
     def test_static_api(self):
         with static_guard():
             with paddle.static.program_guard(paddle.static.Program()):
@@ -4719,6 +4720,7 @@ def test_base_api(self):
             out_ref = ref_mish(self.x_np)
             np.testing.assert_allclose(out_ref, res[0], rtol=1e-05)
 
+    @test_with_pir_api
     def test_errors(self):
         with static_guard():
             with paddle.static.program_guard(paddle.static.Program()):
@@ -4914,7 +4916,7 @@ def test_check_grad(self):
 create_test_act_fp16_class(TestHardSigmoid, check_pir=True)
 create_test_act_fp16_class(TestSwish)
 create_test_act_fp16_class(TestHardSwish, check_prim=True, check_pir=True)
-create_test_act_fp16_class(TestMish)
+create_test_act_fp16_class(TestMish, check_pir=True)
 create_test_act_fp16_class(
     TestLeakyRelu, check_prim=True, enable_cinn=True, check_pir=True
 )
@@ -5073,7 +5075,7 @@ def test_check_grad(self):
 create_test_act_bf16_class(TestHardSigmoid, check_pir=True)
 create_test_act_bf16_class(TestSwish)
 create_test_act_bf16_class(TestHardSwish, check_prim=True, check_pir=True)
-create_test_act_bf16_class(TestMish)
+create_test_act_bf16_class(TestMish, check_pir=True)
 create_test_act_bf16_class(TestLeakyRelu, check_prim=True, check_pir=True)
 create_test_act_bf16_class(TestLeakyReluAlpha1, check_prim=True)
 create_test_act_bf16_class(TestLeakyReluAlpha2, check_prim=True)
diff --git a/test/legacy_test/test_audio_functions.py b/test/legacy_test/test_audio_functions.py
@@ -21,6 +21,7 @@
 
 import paddle
 import paddle.audio
+from paddle.pir_utils import test_with_pir_api
 
 
 def parameterize(*params):
@@ -29,6 +30,7 @@ def parameterize(*params):
 
 class TestAudioFuncitons(unittest.TestCase):
     def setUp(self):
+        paddle.disable_static()
         self.initParmas()
 
     def initParmas(self):
@@ -52,7 +54,9 @@ def get_wav_data(dtype: str, num_channels: int, num_frames: int):
         self.dtype = "float32"
         self.window_size = 1024
         waveform_tensor = get_wav_data(
-            self.dtype, self.num_channels, num_frames=self.duration * self.sr
+            self.dtype,
+            self.num_channels,
+            num_frames=int(self.duration * self.sr),
         )
         self.waveform = waveform_tensor.numpy()
 
@@ -86,6 +90,56 @@ def test_audio_function(self, val: float, htk_flag: bool):
             decibel_paddle.numpy(), decibel_paddle, decimal=5
         )
 
+    @parameterize([1.0, 3.0, 9.0, 25.0], [True, False])
+    @test_with_pir_api
+    def test_audio_function_static(self, val: float, htk_flag: bool):
+        paddle.enable_static()
+        main = paddle.static.Program()
+        startup = paddle.static.Program()
+        with paddle.static.program_guard(main, startup):
+            mel_paddle_tensor = paddle.audio.functional.hz_to_mel(
+                paddle.to_tensor([val]), htk_flag
+            )
+
+            hz_paddle_tensor = paddle.audio.functional.mel_to_hz(
+                paddle.to_tensor([val]), htk_flag
+            )
+
+            decibel_paddle = paddle.audio.functional.power_to_db(
+                paddle.to_tensor([val])
+            )
+
+            exe = paddle.static.Executor()
+            (
+                mel_paddle_tensor_ret,
+                hz_paddle_tensor_ret,
+                decibel_paddle_ret,
+            ) = exe.run(
+                main,
+                fetch_list=[
+                    mel_paddle_tensor,
+                    hz_paddle_tensor,
+                    decibel_paddle,
+                ],
+            )
+
+            mel_librosa = librosa.hz_to_mel(val, htk_flag)
+            np.testing.assert_almost_equal(
+                mel_paddle_tensor_ret, mel_librosa, decimal=4
+            )
+
+            hz_librosa = librosa.mel_to_hz(val, htk_flag)
+            np.testing.assert_almost_equal(
+                hz_paddle_tensor_ret, hz_librosa, decimal=4
+            )
+
+            decibel_librosa = librosa.power_to_db(val)
+            np.testing.assert_almost_equal(
+                decibel_paddle_ret, decibel_librosa, decimal=5
+            )
+
+        paddle.disable_static()
+
     @parameterize(
         [64, 128, 256], [0.0, 0.5, 1.0], [10000, 11025], [False, True]
     )
@@ -102,6 +156,33 @@ def test_audio_function_mel(
             paddle_mel_freq, librosa_mel_freq, decimal=3
         )
 
+    @parameterize(
+        [64, 128, 256], [0.0, 0.5, 1.0], [10000, 11025], [False, True]
+    )
+    # TODO(MarioLulab) May cause precision error. Fix it soon
+    # @test_with_pir_api
+    def test_audio_function_mel_static(
+        self, n_mels: int, f_min: float, f_max: float, htk_flag: bool
+    ):
+        paddle.enable_static()
+        main = paddle.static.Program()
+        startup = paddle.static.Program()
+        with paddle.static.program_guard(main, startup):
+            paddle_mel_freq = paddle.audio.functional.mel_frequencies(
+                n_mels, f_min, f_max, htk_flag, 'float64'
+            )
+
+        exe = paddle.static.Executor()
+        (paddle_mel_freq_ret,) = exe.run(main, fetch_list=[paddle_mel_freq])
+        librosa_mel_freq = librosa.mel_frequencies(
+            n_mels, f_min, f_max, htk_flag
+        )
+        np.testing.assert_almost_equal(
+            paddle_mel_freq_ret, librosa_mel_freq, decimal=3
+        )
+
+        paddle.disable_static()
+
     @parameterize([8000, 16000], [64, 128, 256])
     def test_audio_function_fft(self, sr: int, n_fft: int):
         librosa_fft = librosa.fft_frequencies(sr, n_fft)
